Jonathan A Scott

6 Publications

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[6]
2026 | Published | Thesis | PhD | IST-REx-ID: 21198 | OA
Scott, Jonathan A. Data Heterogeneity and Personalization in Federated Learning. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21198.
[Published Version] View | Files available | DOI
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20819 | OA
Scott, Jonathan A., et al. “Differentially Private Federated K-Means Clustering with Server-Side Data.” 42nd International Conference on Machine Learning, vol. 267, ML Research Press, 2025, pp. 53757–90.
[Published Version] View | Files available | arXiv
 
[4]
2025 | Draft | Preprint | IST-REx-ID: 21207 | OA
Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, doi:10.48550/ARXIV.2505.15579.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott, Jonathan A., and Áine Cahill. “Improved Modelling of Federated Datasets Using Mixtures-of-Dirichlet-Multinomials.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 44012–37.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott, Jonathan A., et al. “PEFLL: Personalized Federated Learning by Learning to Learn.” 12th International Conference on Learning Representations, OpenReview, 2024.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
Scott, Jonathan A., et al. “Cross-Client Label Propagation for Transductive and Semi-Supervised Federated Learning.” Transactions in Machine Learning, Curran Associates, 2023.
[Preprint] View | Files available | arXiv
 
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6 Publications

Mark all

[6]
2026 | Published | Thesis | PhD | IST-REx-ID: 21198 | OA
Scott, Jonathan A. Data Heterogeneity and Personalization in Federated Learning. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21198.
[Published Version] View | Files available | DOI
 
[5]
2025 | Published | Conference Paper | IST-REx-ID: 20819 | OA
Scott, Jonathan A., et al. “Differentially Private Federated K-Means Clustering with Server-Side Data.” 42nd International Conference on Machine Learning, vol. 267, ML Research Press, 2025, pp. 53757–90.
[Published Version] View | Files available | arXiv
 
[4]
2025 | Draft | Preprint | IST-REx-ID: 21207 | OA
Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, doi:10.48550/ARXIV.2505.15579.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 
[3]
2024 | Published | Conference Paper | IST-REx-ID: 18120 | OA
Scott, Jonathan A., and Áine Cahill. “Improved Modelling of Federated Datasets Using Mixtures-of-Dirichlet-Multinomials.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 44012–37.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Conference Paper | IST-REx-ID: 17411 | OA
Scott, Jonathan A., et al. “PEFLL: Personalized Federated Learning by Learning to Learn.” 12th International Conference on Learning Representations, OpenReview, 2024.
[Published Version] View | Files available | arXiv
 
[1]
2023 | Published | Conference Paper | IST-REx-ID: 12660 | OA
Scott, Jonathan A., et al. “Cross-Client Label Propagation for Transductive and Semi-Supervised Federated Learning.” Transactions in Machine Learning, Curran Associates, 2023.
[Preprint] View | Files available | arXiv
 
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Citation Style: MLA

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